
Helping online shoppers discover handcrafted products with an AI-powered assistant
Smarter Product
Discovery
Higher Engagement
& Conversions
Lighter
Support Ops
About the Company


The Problem Statement


Unstructured Product Discovery
Customers struggled to find the right products due to broad user intent and a large, diverse catalog.


Lack of Personalization
Generic filters and search tools led to poor engagement from high-intent shoppers.


High Support Load
Repetitive queries - gift suggestions, navigation help, order
How LYZR Solved It ?
- Offers personalized gift and product suggestions using recipient and occasion context.
- Guides users via chat flows for popular categories (e.g., name plates, terracotta mugs).
- Uses LLMs to map vague queries (e.g., “eco-friendly gift for sister”) to accurate product categories.
- Fetches real-time product info from a PostgreSQL database, filtered by budget, popularity, and tags.
- Enables seamless order tracking within chat.
- Runs on a FastAPI backend integrated with Lyzr’s NLP stack, deployed in a containerized setup.
The Outcome


Smarter Product Discovery
Customers quickly find relevant handcrafted items through contextual, chat-based journeys.


Higher Engagement & Conversions
Interactive flows and tailored recommendations increase time on site and purchases across key categories


Lighter Support Ops
The AI assistant now handles repeat queries- reducing team workload while improving customer response time.
How Lyzr handled security?


Data Residency
All change management data remains securely within NTT Data’s Azure cloud, ensuring 100% ownership and compliance with regional data laws.


Compliance
The Lyzr Agent Platform is SOC2, GDPR, and ISO 27001 compliant, supporting enterprise-grade data handling and privacy.


Reflection Module
Lyzr’s reflection system minimizes model hallucination, ensuring high-accuracy, reliable recommendations in critical workflows.
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